ArticleApplied clinical informatics2018
The Reliability of Electronic Health Record Data Used for Obstetrical Research.
Article in Applied clinical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effectiveness of Clinical Decision Support Systems on the Appropriate Use of Imaging for Central Nervous System Injuries: A Systematic Review.Applied clinical informatics · 2022Pooled it
- Spatial bias in quality of estimated delivery date records in the electronic health record.JAMIA open · 2026Article
- Development of Longitudinal, Linked Maternal-Infant Cohorts using the Epic Cosmos Electronic Health Record Dataset.medRxiv : the preprint server for health sciences · 2026Article
- Remote Consultations in England During COVID-19: Challenges in Data Quality, Linkage, and Research Validity.Online journal of public health informatics · 2025Article
- Pre-conception clinical risk factors differ between spontaneous and indicated preterm birth in a densely phenotyped EHR cohort.BMC pregnancy and childbirth · 2025Article
- Initial Feeding Method, WIC-Provided Lactation Support, and Breastfeeding Duration at an Urban Pediatric Primary Care Practice.Journal of community health · 2024Article
- Rigour and reproducibility in perinatal and paediatric epidemiologic research using big data.Paediatric and perinatal epidemiology · 2023Article
- Real-Time Breastfeeding Documentation: Timing of Breastfeeding Initiation and Outpatient Duration.Academic pediatrics · 2023Article
- Comparison of electronic versus manual abstraction for 2 standardized perinatal care measures.Journal of the American Medical Informatics Association : JAMIA · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHospital electronic health record (EHR) data are increasingly being called upon for research purposes, yet only recently has it been tested to examine its reliability. Studies that have examined reliability of EHR data for research purposes have varied widely in methods used and field of inquiry, with little reporting of the reliability of perinatal and obstetric variables in the current literature.
objectiveTo assess the reliability of data extracted from a commercially available inpatient EHR as compared with manually abstracted data for common attributes used in obstetrical research.
methodsData extracted through automated EHR reports for 3,250 women who delivered a live infant at a large hospital in the Pacific Northwest were compared with manual chart abstraction for the following perinatal measures: delivery method, labor induction, labor augmentation, cervical ripening, vertex presentation, and postpartum hemorrhage.
resultsAlmost perfect agreement was observed for all four modes of delivery (vacuum assisted: kappa = 0.92; 95% confidence interval [CI] = 0.88-0.95, forceps assisted: kappa = 0.90; 95%CI = 0.76-1.00, cesarean delivery: kappa = 0.91; 95%CI = 0.90-0.93, and spontaneous vaginal delivery: kappa = 0.91; 95%CI = 0.90-0.93). Cervical ripening demonstrated substantial agreement (kappa = 0.77; 95%CI = 0.73-0.80); labor induction (kappa = 0.65; 95%CI = 0.62-0.68) and augmentation (kappa = 0.54; 95%CI = 0.49-0.58) demonstrated moderate agreement between the two data sources. Vertex presentation (kappa = 0.35; 95%CI = 0.31-0.40) and post-partum hemorrhage (kappa = 0.21; 95%CI = 0.13-0.28) demonstrated fair agreement.
conclusionOur study demonstrates variability in the reliability of obstetrical data collected and reported through the EHR. While delivery method was satisfactorily reliable in our sample, other examined perinatal measures were less so when compared with manual chart abstraction. The use of multiple modalities for assessing reliability presents a more consistent and rigorous approach for assessing reliability of data from EHR systems and underscores the importance of requiring validation of automated EHR data for research purposes.
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